基于Vague粗糙集信息熵的属性约简算法

Attribution Reduction Algorithm Based on Information Entropy of Vague Rough Set

针对复杂系统分析中的数据信息冗余问题,提出一种基于Vague粗糙集信息熵的属性约简算法。首先,对Vague粗糙集相关概念进行拓展,提出Vague粗糙集的扩展信息熵和广义信息熵的模型;其次,对基于信息熵的属性重要性度量和属性约简原理进行研究,进而提出了一种基于Vague粗糙集信息熵的监督式属性约简算法;最后,选取UCI数据库对算法性能进行验证,计算结果表明该算法实用有效。

In order to solve data information redundancy algorithm based on information entropy of vague rough set in complex system analysis, an attribution reduction is proposed. Firstly, the concerned concepts of vague rough set are expanded, then the extended information entropy and generalized information entropy are defined. Secondly, the attribution importance measure and attribution reduction principle based on information entropy are studied, and then an attribution reduction algorithm based on generalized information entropy is put forward. Finally, the algorithm quality is verified by applying shown the validity and feasibility. to the chosen UCI database, and the calculation resuh has